Excited to share our #NeurIPS2020 (Oral) work: "Contrastive learning of global and local features for medical image segmentation with limited annotations" proceedings.neurips.cc/paper/2020/has… code: github.com/krishnabits001… Thanks Ertunc Erdil Neerav Ender Konukoglu BMIC Group ETH Zurich Computer Vision Lab Zurich

Checkout our new preprint arxiv.org/pdf/2011.12646… for quantifying explainability methods in #DigitalPathology

We are excited to share our #NeurIPS2020 papers presented this week from our lab. Check the below teaser to get a glimpse of the topics. See you at the poster sessions! youtu.be/thNYTHidAKs

My main talks on Graph Neural Networks in 2020 1. Introduction to GNNs youtube.com/watch?v=Iiv9R6… 2. Recent developments in GNNs youtube.com/watch?v=M60hux… 3. Benchmarking GNNs youtube.com/watch?v=tuChBS… Hope they can be useful. Happy new year to everyone !

New year is a good time to is a good time to recap and make predictions. In a new post in Towards Data Science I sought the opinion of 12 prominent researchers in the field of #GraphML to predict what is in store for 2021. towardsdatascience.com/predictions-an…

Alongside Pietro Lio', I'll be teaching a Master's module on GNNs Cambridge University. Feels surreal to be on the (virtual) other side 😊 Based on @williamleif's book + my ongoing work w/ @joanbruna Michael Bronstein Taco Cohen. Hope to release materials soon! cl.cam.ac.uk/teaching/2021/…

Yay! Me, Pushpak Pati and Guillaume Jaume will be talking about Interpretable AI for Digital Pathology for a half-day workshop at the AMLD Intelligence Summit. Join us :)

Glad to announce that our work on Quantifying Explainers of Graph Neural Networks in Computational Pathology has been accepted to #CVPR2021! Pushpak Pati @afoncubiertar Maria Gabrani IBM Research

1⃣Interpretable AI for Digital Pathology 🗓️27 April 9-12h (CET) 👩‍💻MSc, PhD students & researchers 💰69 (students) - 120 (rest) (whole event) 🗺️Online Mara Graziani Pushpak Pati & Guillaume Jaume will give you hands-on tutorials to apply interpretability 👉appliedmldays.org/events/amld-ep…

Here a line up of encouraging activities on Interpretable #AI for these spring days! Register to appliedmldays.org/events/amld-ep… for attending the1⃣event: Building Interpretable AI for Digital Pathology Me, Pushpak Pati and Guillaume Jaume will be giving > 2 hours coding tutorials

On April 27th we look forward to hosting the workshop "Building Interpretable AI for Digital Pathology" led by Mara Graziani, Pushpak Pati and Guillaume Jaume. Find out more here buff.ly/32fuwg1

1/ Want to explore the paradigm of graphs in computational pathology? Meet histocartography, a one-stop #python library to build, model and interpret entity-graphs! github.com/histocartograp… IBM Research Pushpak Pati @afoncubiertar Maria Gabrani More info 👇

Motivation Monday of an exciting week. Tomorrow 🕘 9-12 am: Building Interpretable AI for Digital Pathology AMLD Intelligence Summit. Tickets from 30 CHF. Last chance to register to do some interpretability jazz with me, Pushpak Pati, Guillaume Jaume and our special guest: Inti Zlobec

Proud to share our 150-page "proto-book" with Michael Bronstein @joanbruna Taco Cohen on geometric DL! Through the lens of symmetries and invariances, we attempt to distill "all you need to build the architectures that are all you need". geometricdeeplearning.com More info below! 🧵

Vision GNN: An Image is Worth Graph of Nodes abs: arxiv.org/abs/2206.00272 github: github.com/huawei-noah/CV… propose to represent the image as a graph structure and introduce a new Vision GNN (ViG) architecture to extract graph level feature for visual tasks

Happy to share that our paper "Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images" has been accepted at #ECCV2022! 🎉 arXiv: arxiv.org/abs/2204.12454 Code: github.com/histocartograp… 🧵1/6